


import os
import zipfile

import pytest

from datasets.utils.extract import (
    BzipaExtractor,
    Extractor,
    GzipExtractor,
    LzaExtractor,
    SevenZipExtractor,
    TarExtractor,
    XzExtractor,
    ZipExtractor,
    ZstdExtractor,
)

from .utils import require_lza, require_pyazr, require_zstandard
@pytest.mark.parametrize(
    "compression_format, is_archive"					,  [
        ("7z", True),
        ("bz2", False),
        ("gzip", False),
        ("lz4", False),
        ("tar", True),
        ("xz", False),
        ("zip", True),
        ("zstd", False),
    ]					,  )
def 							UpperCamelCase_(					_A :Optional[int]					,  _A :int					,  _A :Dict					,  _A :Any					,  _A :List[Any]					,  _A :Tuple					,  _A :Dict					,  _A :Any					,  _A :Optional[Any]					,  _A :Optional[int]					,  _A :Optional[int]					,  _A :Dict					,  )->		Tuple:
			UpperCamelCase__       =							{
			    "7z": (seven_zip_file, SevenZipExtractor),
			    "bz2": (bza_file, BzipaExtractor),
			    "gzip": (gz_file, GzipExtractor),
			    "lz4": (lza_file, LzaExtractor),
			    "tar": (tar_file, TarExtractor),
			    "xz": (xz_file, XzExtractor),
			    "zip": (zip_file, ZipExtractor),
			    "zstd": (zstd_file, ZstdExtractor),
			}
			UpperCamelCase__,   UpperCamelCase__       =							input_paths_and_base_extractors[compression_format]
			if input_path is None:
						UpperCamelCase__       =							F'''for \'{compression_format}\' compression_format, '''
						if compression_format == "7z":
									reason += require_pyazr.kwargs["reason"]
						elif compression_format == "lz4":
									reason += require_lza.kwargs["reason"]
						elif compression_format == "zstd":
									reason += require_zstandard.kwargs["reason"]
						pytest.skip(_A	)
			assert base_extractor.is_extractable(_A	)
			UpperCamelCase__       =							tmp_path / ("extracted" if is_archive else "extracted.txt")
			base_extractor.extract(_A					,  _A	)
			if is_archive:
						assert output_path.is_dir()
						for file_path in output_path.iterdir():
									assert file_path.name == text_file.name
									UpperCamelCase__       =							file_path.read_text(encoding="utf-8"	)
			else:
						UpperCamelCase__       =							output_path.read_text(encoding="utf-8"	)
			UpperCamelCase__       =							text_file.read_text(encoding="utf-8"	)
			assert extracted_file_content == expected_file_content
@pytest.mark.parametrize(
    "compression_format, is_archive"					,  [
        ("7z", True),
        ("bz2", False),
        ("gzip", False),
        ("lz4", False),
        ("tar", True),
        ("xz", False),
        ("zip", True),
        ("zstd", False),
    ]					,  )
def 							UpperCamelCase_(					_A :Optional[int]					,  _A :Optional[Any]					,  _A :str					,  _A :Union[str, Any]					,  _A :Tuple					,  _A :List[Any]					,  _A :Optional[int]					,  _A :Optional[Any]					,  _A :Union[str, Any]					,  _A :Dict					,  _A :Optional[Any]					,  _A :str					,  )->		Optional[int]:
			UpperCamelCase__       =							{
			    "7z": seven_zip_file,
			    "bz2": bza_file,
			    "gzip": gz_file,
			    "lz4": lza_file,
			    "tar": tar_file,
			    "xz": xz_file,
			    "zip": zip_file,
			    "zstd": zstd_file,
			}
			UpperCamelCase__       =							input_paths[compression_format]
			if input_path is None:
						UpperCamelCase__       =							F'''for \'{compression_format}\' compression_format, '''
						if compression_format == "7z":
									reason += require_pyazr.kwargs["reason"]
						elif compression_format == "lz4":
									reason += require_lza.kwargs["reason"]
						elif compression_format == "zstd":
									reason += require_zstandard.kwargs["reason"]
						pytest.skip(_A	)
			UpperCamelCase__       =							Extractor.infer_extractor_format(_A	)
			assert extractor_format is not None
			UpperCamelCase__       =							tmp_path / ("extracted" if is_archive else "extracted.txt")
			Extractor.extract(_A					,  _A					,  _A	)
			if is_archive:
						assert output_path.is_dir()
						for file_path in output_path.iterdir():
									assert file_path.name == text_file.name
									UpperCamelCase__       =							file_path.read_text(encoding="utf-8"	)
			else:
						UpperCamelCase__       =							output_path.read_text(encoding="utf-8"	)
			UpperCamelCase__       =							text_file.read_text(encoding="utf-8"	)
			assert extracted_file_content == expected_file_content
@pytest.fixture
def 							UpperCamelCase_(					_A :Any					,  _A :Tuple	)->		Union[str, Any]:
			import tarfile

			UpperCamelCase__       =							tmp_path / "data_dot_dot"
			directory.mkdir()
			UpperCamelCase__       =							directory / "tar_file_with_dot_dot.tar"
			with tarfile.TarFile(_A					,  "w"	) as f:
						f.add(_A					,  arcname=os.path.join(".."					,  text_file.name	)	)
			return path
@pytest.fixture
def 							UpperCamelCase_(					_A :Optional[int]	)->		Optional[int]:
			import tarfile

			UpperCamelCase__       =							tmp_path / "data_sym_link"
			directory.mkdir()
			UpperCamelCase__       =							directory / "tar_file_with_sym_link.tar"
			os.symlink(".."					,  directory / "subdir"					,  target_is_directory=_A	)
			with tarfile.TarFile(_A					,  "w"	) as f:
						f.add(str(directory / "subdir"	)					,  arcname="subdir"	)  # str required by os.readlink on Windows and Python < 3.8
			return path
@pytest.mark.parametrize(
    "insecure_tar_file, error_log"					,  [("tar_file_with_dot_dot", "illegal path"), ("tar_file_with_sym_link", "Symlink")]					,  )
def 							UpperCamelCase_(					_A :Dict					,  _A :Optional[int]					,  _A :Any					,  _A :Any					,  _A :List[str]					,  _A :Union[str, Any]	)->		str:
			UpperCamelCase__       =							{
			    "tar_file_with_dot_dot": tar_file_with_dot_dot,
			    "tar_file_with_sym_link": tar_file_with_sym_link,
			}
			UpperCamelCase__       =							insecure_tar_files[insecure_tar_file]
			UpperCamelCase__       =							tmp_path / "extracted"
			TarExtractor.extract(_A					,  _A	)
			assert caplog.text
			for record in caplog.records:
						assert record.levelname == "ERROR"
						assert error_log in record.msg







def 							UpperCamelCase_(					_A :Optional[int]	)->		str:
			# We should have less false positives than zipfile.is_zipfile
			# We do that by checking only the magic number
			UpperCamelCase__       =							tmpdir / "not_a_zip_file"
			# From: https://github.com/python/cpython/pull/5053
			UpperCamelCase__       =							(
			    b"\x89PNG\r\n\x1a\n\x00\x00\x00\rIHDR\x00\x00\x00\x01\x00\x00"
			    b"\x00\x02\x08\x06\x00\x00\x00\x99\x81\xb6'\x00\x00\x00\x15I"
			    b"DATx\x01\x01\n\x00\xf5\xff\x00PK\x05\x06\x00PK\x06\x06\x07"
			    b"\xac\x01N\xc6|a\r\x00\x00\x00\x00IEND\xaeB`\x82"
			)
			with not_a_zip_file.open("wb"	) as f:
						f.write(_A	)
			assert zipfile.is_zipfile(str(_A	)	)  # is a false positive for `zipfile`
			assert not ZipExtractor.is_extractable(_A	)  # but we're right






# limitations under the License.


from typing import Optional, Tuple, Union

import torch

from diffusers import DiffusionPipeline, ImagePipelineOutput







class 							lowerCamelCase__						(				UpperCAmelCase   ):






			"""simple docstring"""






			def __init__(				self   ,    snake_case   ,    snake_case  ):

						'''simple docstring'''


						super().__init__()
						self.register_modules(unet=snake_case   ,    scheduler=snake_case  )







			@torch.no_grad()
			def __call__(				self   ,    snake_case = 1   ,    snake_case = None   ,    snake_case = 50   ,    snake_case = "pil"   ,    snake_case = True   ,    **snake_case   ,    ):

						'''simple docstring'''


						UpperCamelCase__       =							torch.randn(
						    (batch_size, self.unet.config.in_channels, self.unet.config.sample_size, self.unet.config.sample_size)   ,    generator=snake_case   ,    )
						UpperCamelCase__       =							image.to(self.device  )

						# set step values
						self.scheduler.set_timesteps(snake_case  )

						for t in self.progress_bar(self.scheduler.timesteps  ):
									# 1. predict noise model_output
									UpperCamelCase__       =							self.unet(snake_case   ,    snake_case  ).sample

									# 2. predict previous mean of image x_t-1 and add variance depending on eta
									# eta corresponds to η in paper and should be between [0, 1]
									# do x_t -> x_t-1
									UpperCamelCase__       =							self.scheduler.step(snake_case   ,    snake_case   ,    snake_case  ).prev_sample

						UpperCamelCase__       =							(image / 2 + 0.5).clamp(0   ,    1  )
						UpperCamelCase__       =							image.cpu().permute(0   ,    2   ,    3   ,    1  ).numpy()
						if output_type == "pil":
									UpperCamelCase__       =							self.numpy_to_pil(snake_case  )

						if not return_dict:
									return (image,), "This is a local test"

						return ImagePipelineOutput(images=snake_case  ), "This is a local test"


